Articles | Volume 17, issue 22
https://doi.org/10.5194/gmd-17-8321-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-17-8321-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
25 Nov 2024
Model description paper |
| 25 Nov 2024
| 25 Nov 2024
MESSAGEix-Materials v1.1.0: representation of material flows and stocks in an integrated assessment model
International Institute for Applied Systems Analysis, Energy Climate and Environment Programme, Laxenburg, 2361, Austria
Institute of Social Ecology, University of Natural Resources and Life Sciences, Vienna (BOKU), Schottenfeldgasse 29, Vienna, 1070, Austria
Florian Maczek
International Institute for Applied Systems Analysis, Energy Climate and Environment Programme, Laxenburg, 2361, Austria
Jihoon Min
International Institute for Applied Systems Analysis, Energy Climate and Environment Programme, Laxenburg, 2361, Austria
Stefan Frank
International Institute for Applied Systems Analysis, Energy Climate and Environment Programme, Laxenburg, 2361, Austria
Institute for Sustainable Economic Development, University of Natural Resources and Life Sciences, Vienna (BOKU), Feistmantelstraße 4, Vienna, 1180, Austria
Fridolin Glatter
International Institute for Applied Systems Analysis, Energy Climate and Environment Programme, Laxenburg, 2361, Austria
Paul Natsuo Kishimoto
International Institute for Applied Systems Analysis, Energy Climate and Environment Programme, Laxenburg, 2361, Austria
Jan Streeck
Institute of Social Ecology, University of Natural Resources and Life Sciences, Vienna (BOKU), Schottenfeldgasse 29, Vienna, 1070, Austria
Nina Eisenmenger
Institute of Social Ecology, University of Natural Resources and Life Sciences, Vienna (BOKU), Schottenfeldgasse 29, Vienna, 1070, Austria
Dominik Wiedenhofer
Institute of Social Ecology, University of Natural Resources and Life Sciences, Vienna (BOKU), Schottenfeldgasse 29, Vienna, 1070, Austria
Volker Krey
International Institute for Applied Systems Analysis, Energy Climate and Environment Programme, Laxenburg, 2361, Austria
Industrial Ecology Programme and Energy Transitions Initiative, Norwegian University of Science and Technology (NTNU), Trondheim, 7491, Norway
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Felix Jäger, Jonas Schwaab, Yann Quilcaille, Michael Windisch, Jonathan Doelman, Stefan Frank, Mykola Gusti, Petr Havlik, Florian Humpenöder, Andrey Lessa Derci Augustynczik, Christoph Müller, Kanishka Balu Narayan, Ryan Sebastian Padrón, Alexander Popp, Detlef van Vuuren, Michael Wögerer, and Sonia Isabelle Seneviratne
Earth Syst. Dynam., 15, 1055–1071, https://doi.org/10.5194/esd-15-1055-2024, https://doi.org/10.5194/esd-15-1055-2024, 2024
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Climate change mitigation strategies developed with socioeconomic models rely on the widespread (re)planting of trees to limit global warming below 2°. However, most of these models neglect climate-driven shifts in forest damage like fires. By assessing existing mitigation scenarios, we show the exposure of projected forestation areas to fire-promoting weather conditions. Our study highlights the problem of ignoring climate-driven shifts in forest damage and ways to address it.
Eric Galbraith, Abdullah-Al Faisal, Tanya Matitia, William Fajzel, Ian Hatton, Helmut Haberl, Fridolin Krausmann, and Dominik Wiedenhofer
EGUsphere, https://doi.org/10.5194/egusphere-2024-1133, https://doi.org/10.5194/egusphere-2024-1133, 2024
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The technosphere, including buildings, infrastructure and all other non-living human creations, has become a major part of the Earth system. Here we provide a refined definition of the technosphere, and an end-use classification aligned with the physical outcomes of human activities. We use these definitions to describe the composition and spatial distribution of technosphere mass, and discuss the exponential character of its growth since 1900, which presents a challenge for sustainability.
Muhammad Awais, Adriano Vinca, Edward Byers, Stefan Frank, Oliver Fricko, Esther Boere, Peter Burek, Miguel Poblete Cazenave, Paul Natsuo Kishimoto, Alessio Mastrucci, Yusuke Satoh, Amanda Palazzo, Madeleine McPherson, Keywan Riahi, and Volker Krey
Geosci. Model Dev., 17, 2447–2469, https://doi.org/10.5194/gmd-17-2447-2024, https://doi.org/10.5194/gmd-17-2447-2024, 2024
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Climate change, population growth, and depletion of natural resources all pose complex and interconnected challenges. Our research offers a novel model that can help in understanding the interplay of these aspects, providing policymakers with a more robust tool for making informed future decisions. The study highlights the significance of incorporating climate impacts within large-scale global integrated assessments, which can help us in generating more climate-resilient scenarios.
Adriano Vinca, Simon Parkinson, Edward Byers, Peter Burek, Zarrar Khan, Volker Krey, Fabio A. Diuana, Yaoping Wang, Ansir Ilyas, Alexandre C. Köberle, Iain Staffell, Stefan Pfenninger, Abubakr Muhammad, Andrew Rowe, Roberto Schaeffer, Narasimha D. Rao, Yoshihide Wada, Ned Djilali, and Keywan Riahi
Geosci. Model Dev., 13, 1095–1121, https://doi.org/10.5194/gmd-13-1095-2020, https://doi.org/10.5194/gmd-13-1095-2020, 2020
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This article describes a newly developed numerical model that can assess impacts of long-term policies for the energy, water and land (WEL) sectors at the scale of a river basin. We show the importance of having an integrated method when jointly considering multiple policies as opposed to conventional sectoral analysis. This model can be useful for studying river basins, such as the Indus basin, that are exposed to challenges over WEL sectors, like water scarcity or food and energy access.
Matthew J. Gidden, Keywan Riahi, Steven J. Smith, Shinichiro Fujimori, Gunnar Luderer, Elmar Kriegler, Detlef P. van Vuuren, Maarten van den Berg, Leyang Feng, David Klein, Katherine Calvin, Jonathan C. Doelman, Stefan Frank, Oliver Fricko, Mathijs Harmsen, Tomoko Hasegawa, Petr Havlik, Jérôme Hilaire, Rachel Hoesly, Jill Horing, Alexander Popp, Elke Stehfest, and Kiyoshi Takahashi
Geosci. Model Dev., 12, 1443–1475, https://doi.org/10.5194/gmd-12-1443-2019, https://doi.org/10.5194/gmd-12-1443-2019, 2019
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We present a suite of nine scenarios of future emissions trajectories of anthropogenic sources for use in CMIP6. Integrated assessment model results are provided for each scenario with consistent transitions from the historical data to future trajectories. We find that the set of scenarios enables the exploration of a variety of warming pathways. A wide range of scenario data products are provided for the CMIP6 scientific community including global, regional, and gridded emissions datasets.
Related subject area
Integrated assessment modeling
GCAM–GLORY v1.0: representing global reservoir water storage in a multi-sector human–Earth system model
pathways-ensemble-analysis v1.0.0: an open-source library for systematic and robust analysis of pathways ensembles
CLASH – Climate-responsive Land Allocation model with carbon Storage and Harvests
Carbon Monitor Power-Simulators (CMP-SIM v1.0) across countries: a data-driven approach to simulate daily power generation
Intercomparison of multiple two-way coupled meteorology and air quality models (WRF v4.1.1–CMAQ v5.3.1, WRF–Chem v4.1.1, and WRF v3.7.1–CHIMERE v2020r1) in eastern China
MESSAGEix-GLOBIOM nexus module: integrating water sector and climate impacts
Minimum-variance-based outlier detection method using forward-search model error in geodetic networks
Modelling long-term industry energy demand and CO2 emissions in the system context using REMIND (version 3.1.0)
Bidirectional coupling of the long-term integrated assessment model REgional Model of INvestments and Development (REMIND) v3.0.0 with the hourly power sector model Dispatch and Investment Evaluation Tool with Endogenous Renewables (DIETER) v1.0.2
GCAM-CDR v1.0: enhancing the representation of carbon dioxide removal technologies and policies in an integrated assessment model
The IPCC Sixth Assessment Report WGIII climate assessment of mitigation pathways: from emissions to global temperatures
Cyclone generation Algorithm including a THERmodynamic module for Integrated National damage Assessment (CATHERINA 1.0) compatible with Coupled Model Intercomparison Project (CMIP) climate data
A tool for air pollution scenarios (TAPS v1.0) to enable global, long-term, and flexible study of climate and air quality policies
Improved CASA model based on satellite remote sensing data: simulating net primary productivity of Qinghai Lake basin alpine grassland
Pixel-level parameter optimization of a terrestrial biosphere model for improving estimation of carbon fluxes with an efficient model–data fusion method and satellite-derived LAI and GPP data
Climate Services Toolbox (CSTools) v4.0: from climate forecasts to climate forecast information
TIM: modelling pathways to meet Ireland's long-term energy system challenges with the TIMES-Ireland Model (v1.0)
ANEMI_Yangtze v1.0: a coupled human–natural systems model for the Yangtze Economic Belt – model description
Nested leave-two-out cross-validation for the optimal crop yield model selection
GCAM-USA v5.3_water_dispatch: integrated modeling of subnational US energy, water, and land systems within a global framework
GOBLIN version 1.0: a land balance model to identify national agriculture and land use pathways to climate neutrality via backcasting
Globally consistent assessment of economic impacts of wildfires in CLIMADA v2.2
REMIND2.1: transformation and innovation dynamics of the energy-economic system within climate and sustainability limits
Parallel gridded simulation framework for DSSAT-CSM (version 4.7.5.21) using MPI and NetCDF
Estimating global land system impacts of timber plantations using MAgPIE 4.3.5
Mengqi Zhao, Thomas B. Wild, Neal T. Graham, Son H. Kim, Matthew Binsted, A. F. M. Kamal Chowdhury, Siwa Msangi, Pralit L. Patel, Chris R. Vernon, Hassan Niazi, Hong-Yi Li, and Guta W. Abeshu
Geosci. Model Dev., 17, 5587–5617, https://doi.org/10.5194/gmd-17-5587-2024, https://doi.org/10.5194/gmd-17-5587-2024, 2024
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The Global Change Analysis Model (GCAM) simulates the world’s climate–land–energy–water system interactions , but its reservoir representation is limited. We developed the GLObal Reservoir Yield (GLORY) model to provide GCAM with information on the cost of supplying water based on reservoir construction costs, climate and demand conditions, and reservoir expansion potential. GLORY enhances our understanding of future reservoir capacity needs to meet human demands in a changing climate.
Lara Welder, Neil Grant, and Matthew J. Gidden
EGUsphere, https://doi.org/10.5194/egusphere-2024-761, https://doi.org/10.5194/egusphere-2024-761, 2024
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Pathways investigating the link between emissions and global warming have been continuously used to inform climate policy. We have developed a tool that can facilitate the systematic and robust analysis of ensembles of such pathways. We describe the structure of this tool and then show an illustrative application of it. The application indicates the usefulness of the tool to the research community and shows how it can be used to establish best-practices.
Tommi Ekholm, Nadine-Cyra Freistetter, Aapo Rautiainen, and Laura Thölix
Geosci. Model Dev., 17, 3041–3062, https://doi.org/10.5194/gmd-17-3041-2024, https://doi.org/10.5194/gmd-17-3041-2024, 2024
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CLASH is a numerical model that portrays land allocation between different uses, land carbon stocks, and agricultural and forestry production globally. CLASH can help in examining the role of land use in mitigating climate change, providing food and biogenic raw materials for the economy, and conserving primary ecosystems. Our demonstration with CLASH confirms that reduction of animal-based food, shifting croplands and storing carbon in forests are effective ways to mitigate climate change.
Léna Gurriaran, Yannig Goude, Katsumasa Tanaka, Biqing Zhu, Zhu Deng, Xuanren Song, and Philippe Ciais
Geosci. Model Dev., 17, 2663–2682, https://doi.org/10.5194/gmd-17-2663-2024, https://doi.org/10.5194/gmd-17-2663-2024, 2024
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We developed a data-driven model simulating daily regional power demand based on climate and socioeconomic variables. Our model was applied to eight countries or regions (Australia, Brazil, China, EU, India, Russia, South Africa, US), identifying influential factors and their relationship with power demand. Our findings highlight the significance of economic indicators in addition to temperature, showcasing country-specific variations. This research aids energy planning and emission reduction.
Chao Gao, Xuelei Zhang, Aijun Xiu, Qingqing Tong, Hongmei Zhao, Shichun Zhang, Guangyi Yang, Mengduo Zhang, and Shengjin Xie
Geosci. Model Dev., 17, 2471–2492, https://doi.org/10.5194/gmd-17-2471-2024, https://doi.org/10.5194/gmd-17-2471-2024, 2024
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A comprehensive comparison study is conducted targeting the performances of three two-way coupled meteorology and air quality models (WRF-CMAQ, WRF-Chem, and WRF-CHIMERE) for eastern China during 2017. The impacts of aerosol–radiation–cloud interactions on these models’ results are evaluated against satellite and surface observations. Further improvements to the calculation of aerosol–cloud interactions in these models are crucial to ensure more accurate and timely air quality forecasts.
Muhammad Awais, Adriano Vinca, Edward Byers, Stefan Frank, Oliver Fricko, Esther Boere, Peter Burek, Miguel Poblete Cazenave, Paul Natsuo Kishimoto, Alessio Mastrucci, Yusuke Satoh, Amanda Palazzo, Madeleine McPherson, Keywan Riahi, and Volker Krey
Geosci. Model Dev., 17, 2447–2469, https://doi.org/10.5194/gmd-17-2447-2024, https://doi.org/10.5194/gmd-17-2447-2024, 2024
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Climate change, population growth, and depletion of natural resources all pose complex and interconnected challenges. Our research offers a novel model that can help in understanding the interplay of these aspects, providing policymakers with a more robust tool for making informed future decisions. The study highlights the significance of incorporating climate impacts within large-scale global integrated assessments, which can help us in generating more climate-resilient scenarios.
Utkan M. Durdağ
Geosci. Model Dev., 17, 2187–2196, https://doi.org/10.5194/gmd-17-2187-2024, https://doi.org/10.5194/gmd-17-2187-2024, 2024
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This study introduces a novel approach to outlier detection in geodetic networks, challenging conventional and robust methods. By treating outliers as unknown parameters within the Gauss–Markov model and exploring numerous outlier combinations, this approach prioritizes minimal variance and eliminates iteration dependencies. The mean success rate (MSR) comparisons highlight its effectiveness, improving the MSR by 40–45 % for multiple outliers.
Michaja Pehl, Felix Schreyer, and Gunnar Luderer
Geosci. Model Dev., 17, 2015–2038, https://doi.org/10.5194/gmd-17-2015-2024, https://doi.org/10.5194/gmd-17-2015-2024, 2024
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We extend the REMIND model (used to investigate climate mitigation strategies) by an industry module that represents cement, chemical, steel, and other industries. We also present a method for deriving scenarios of industry subsector activity and energy demand, consistent with established socioeconomic scenarios, allowing us to investigate the different climate change mitigation challenges and strategies in industry subsectors in the context of the entire energy–economy–climate system.
Chen Chris Gong, Falko Ueckerdt, Robert Pietzcker, Adrian Odenweller, Wolf-Peter Schill, Martin Kittel, and Gunnar Luderer
Geosci. Model Dev., 16, 4977–5033, https://doi.org/10.5194/gmd-16-4977-2023, https://doi.org/10.5194/gmd-16-4977-2023, 2023
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To mitigate climate change, the global economy must drastically reduce its greenhouse gas emissions, for which the power sector plays a key role. Until now, long-term models which simulate this transformation cannot always accurately depict the power sector due to a lack of resolution. Our work bridges this gap by linking a long-term model to an hourly model. The result is an almost full harmonization of the models in generating a power sector mix until 2100 with hourly resolution.
David R. Morrow, Raphael Apeaning, and Garrett Guard
Geosci. Model Dev., 16, 1105–1118, https://doi.org/10.5194/gmd-16-1105-2023, https://doi.org/10.5194/gmd-16-1105-2023, 2023
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GCAM-CDR is a variant of the Global Change Analysis Model that makes it easier to study the roles that carbon dioxide removal (CDR) might play in climate policy. Building on GCAM 5.4, GCAM-CDR adds several extra technologies to permanently remove carbon dioxide from the air and enables users to simulate a wider range of CDR-related policies and controls.
Jarmo S. Kikstra, Zebedee R. J. Nicholls, Christopher J. Smith, Jared Lewis, Robin D. Lamboll, Edward Byers, Marit Sandstad, Malte Meinshausen, Matthew J. Gidden, Joeri Rogelj, Elmar Kriegler, Glen P. Peters, Jan S. Fuglestvedt, Ragnhild B. Skeie, Bjørn H. Samset, Laura Wienpahl, Detlef P. van Vuuren, Kaj-Ivar van der Wijst, Alaa Al Khourdajie, Piers M. Forster, Andy Reisinger, Roberto Schaeffer, and Keywan Riahi
Geosci. Model Dev., 15, 9075–9109, https://doi.org/10.5194/gmd-15-9075-2022, https://doi.org/10.5194/gmd-15-9075-2022, 2022
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Assessing hundreds or thousands of emission scenarios in terms of their global mean temperature implications requires standardised procedures of infilling, harmonisation, and probabilistic temperature assessments. We here present the open-source
climate-assessmentworkflow that was used in the IPCC AR6 Working Group III report. The paper provides key insight for anyone wishing to understand the assessment of climate outcomes of mitigation pathways in the context of the Paris Agreement.
Théo Le Guenedal, Philippe Drobinski, and Peter Tankov
Geosci. Model Dev., 15, 8001–8039, https://doi.org/10.5194/gmd-15-8001-2022, https://doi.org/10.5194/gmd-15-8001-2022, 2022
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The CATHERINA model produces simulations of cyclone-related annualized damage costs at a country level from climate data and open-source socioeconomic indicators. The framework couples statistical and physical modeling of tropical cyclones to bridge the gap between general circulation and integrated assessment models providing a precise description of tropical-cyclone-related damages.
William Atkinson, Sebastian D. Eastham, Y.-H. Henry Chen, Jennifer Morris, Sergey Paltsev, C. Adam Schlosser, and Noelle E. Selin
Geosci. Model Dev., 15, 7767–7789, https://doi.org/10.5194/gmd-15-7767-2022, https://doi.org/10.5194/gmd-15-7767-2022, 2022
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Understanding policy effects on human-caused air pollutant emissions is key for assessing related health impacts. We develop a flexible scenario tool that combines updated emissions data sets, long-term economic modeling, and comprehensive technology pathways to clarify the impacts of climate and air quality policies. Results show the importance of both policy levers in the future to prevent long-term emission increases from offsetting near-term air quality improvements from existing policies.
Chengyong Wu, Kelong Chen, Chongyi E, Xiaoni You, Dongcai He, Liangbai Hu, Baokang Liu, Runke Wang, Yaya Shi, Chengxiu Li, and Fumei Liu
Geosci. Model Dev., 15, 6919–6933, https://doi.org/10.5194/gmd-15-6919-2022, https://doi.org/10.5194/gmd-15-6919-2022, 2022
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The traditional Carnegie–Ames–Stanford Approach (CASA) model driven by multisource data such as meteorology, soil, and remote sensing (RS) has notable disadvantages. We drove the CASA using RS data and conducted a case study of the Qinghai Lake basin alpine grassland. The simulated result is similar to published and measured net primary productivity (NPP). It may provide a reference for simulating vegetation NPP to satisfy the requirements of accounting carbon stocks and other applications.
Rui Ma, Jingfeng Xiao, Shunlin Liang, Han Ma, Tao He, Da Guo, Xiaobang Liu, and Haibo Lu
Geosci. Model Dev., 15, 6637–6657, https://doi.org/10.5194/gmd-15-6637-2022, https://doi.org/10.5194/gmd-15-6637-2022, 2022
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Parameter optimization can improve the accuracy of modeled carbon fluxes. Few studies conducted pixel-level parameterization because it requires a high computational cost. Our paper used high-quality spatial products to optimize parameters at the pixel level, and also used the machine learning method to improve the speed of optimization. The results showed that there was significant spatial variability of parameters and we also improved the spatial pattern of carbon fluxes.
Núria Pérez-Zanón, Louis-Philippe Caron, Silvia Terzago, Bert Van Schaeybroeck, Llorenç Lledó, Nicolau Manubens, Emmanuel Roulin, M. Carmen Alvarez-Castro, Lauriane Batté, Pierre-Antoine Bretonnière, Susana Corti, Carlos Delgado-Torres, Marta Domínguez, Federico Fabiano, Ignazio Giuntoli, Jost von Hardenberg, Eroteida Sánchez-García, Verónica Torralba, and Deborah Verfaillie
Geosci. Model Dev., 15, 6115–6142, https://doi.org/10.5194/gmd-15-6115-2022, https://doi.org/10.5194/gmd-15-6115-2022, 2022
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CSTools (short for Climate Service Tools) is an R package that contains process-based methods for climate forecast calibration, bias correction, statistical and stochastic downscaling, optimal forecast combination, and multivariate verification, as well as basic and advanced tools to obtain tailored products. In addition to describing the structure and methods in the package, we also present three use cases to illustrate the seasonal climate forecast post-processing for specific purposes.
Olexandr Balyk, James Glynn, Vahid Aryanpur, Ankita Gaur, Jason McGuire, Andrew Smith, Xiufeng Yue, and Hannah Daly
Geosci. Model Dev., 15, 4991–5019, https://doi.org/10.5194/gmd-15-4991-2022, https://doi.org/10.5194/gmd-15-4991-2022, 2022
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Ireland has significantly increased its climate mitigation ambition, with a recent commitment to reduce greenhouse gases by an average of 7 % yr-1 in the period to 2030 and a net-zero target for 2050. This article describes the TIMES-Ireland model (TIM) developed to inform Ireland's energy system decarbonisation challenge. The paper also outlines a priority list of future model developments to better meet the challenge, taking into account equity, cost-effectiveness, and technical feasibility.
Haiyan Jiang, Slobodan P. Simonovic, and Zhongbo Yu
Geosci. Model Dev., 15, 4503–4528, https://doi.org/10.5194/gmd-15-4503-2022, https://doi.org/10.5194/gmd-15-4503-2022, 2022
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The Yangtze Economic Belt is one of the most dynamic regions of China. The fast urbanization and strong economic growth in the region pose severe challenges for its sustainable development. To improve our understanding of the interactions among coupled human–natural systems in the Belt and to provide the foundation for science-based policy-making for the sustainable development of the Belt, we developed an integrated system-dynamics-based simulation model (ANEMI_Yangtze) for the Belt.
Thi Lan Anh Dinh and Filipe Aires
Geosci. Model Dev., 15, 3519–3535, https://doi.org/10.5194/gmd-15-3519-2022, https://doi.org/10.5194/gmd-15-3519-2022, 2022
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We proposed the leave-two-out method (i.e. one particular implementation of the nested cross-validation) to determine the optimal statistical crop model (using the validation dataset) and estimate its true generalization ability (using the testing dataset). This approach is applied to two examples (robusta coffee in Cu M'gar and grain maize in France). The results suggested that the simple models are more suitable in crop modelling where a limited number of samples is available.
Matthew Binsted, Gokul Iyer, Pralit Patel, Neal T. Graham, Yang Ou, Zarrar Khan, Nazar Kholod, Kanishka Narayan, Mohamad Hejazi, Son Kim, Katherine Calvin, and Marshall Wise
Geosci. Model Dev., 15, 2533–2559, https://doi.org/10.5194/gmd-15-2533-2022, https://doi.org/10.5194/gmd-15-2533-2022, 2022
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GCAM-USA v5.3_water_dispatch is an open-source model that represents key interactions across economic, energy, water, and land systems in a global framework, with subnational detail in the United States. GCAM-USA can be used to explore future changes in demand for (and production of) energy, water, and crops at the state and regional level in the US. This paper describes GCAM-USA and provides four illustrative scenarios to demonstrate the model's capabilities and potential applications.
Colm Duffy, Remi Prudhomme, Brian Duffy, James Gibbons, Cathal O'Donoghue, Mary Ryan, and David Styles
Geosci. Model Dev., 15, 2239–2264, https://doi.org/10.5194/gmd-15-2239-2022, https://doi.org/10.5194/gmd-15-2239-2022, 2022
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The GOBLIN (General Overview for a Backcasting approach of Livestock INtensification) model is a new high-resolution integrated
bottom-upbiophysical land use model capable of identifying broad pathways towards climate neutrality in the agriculture, forestry, and other land use (AFOLU) sector. The model is intended to bridge the gap between hindsight representations of national emissions and much larger globally integrated assessment models.
Samuel Lüthi, Gabriela Aznar-Siguan, Christopher Fairless, and David N. Bresch
Geosci. Model Dev., 14, 7175–7187, https://doi.org/10.5194/gmd-14-7175-2021, https://doi.org/10.5194/gmd-14-7175-2021, 2021
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In light of the dramatic increase in economic impacts due to wildfires, the need for modelling impacts of wildfire damage is ever increasing. Insurance companies, households, humanitarian organisations and governmental authorities are worried by climate risks. In this study we present an approach to modelling wildfire impacts using the open-source modelling platform CLIMADA. All input data are free, public and globally available, ensuring applicability in data-scarce regions of the Global South.
Lavinia Baumstark, Nico Bauer, Falk Benke, Christoph Bertram, Stephen Bi, Chen Chris Gong, Jan Philipp Dietrich, Alois Dirnaichner, Anastasis Giannousakis, Jérôme Hilaire, David Klein, Johannes Koch, Marian Leimbach, Antoine Levesque, Silvia Madeddu, Aman Malik, Anne Merfort, Leon Merfort, Adrian Odenweller, Michaja Pehl, Robert C. Pietzcker, Franziska Piontek, Sebastian Rauner, Renato Rodrigues, Marianna Rottoli, Felix Schreyer, Anselm Schultes, Bjoern Soergel, Dominika Soergel, Jessica Strefler, Falko Ueckerdt, Elmar Kriegler, and Gunnar Luderer
Geosci. Model Dev., 14, 6571–6603, https://doi.org/10.5194/gmd-14-6571-2021, https://doi.org/10.5194/gmd-14-6571-2021, 2021
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This paper presents the new and open-source version 2.1 of the REgional Model of INvestments and Development (REMIND) with the aim of improving code documentation and transparency. REMIND is an integrated assessment model (IAM) of the energy-economic system. By answering questions like
Can the world keep global warming below 2 °C?and, if so,
Under what socio-economic conditions and applying what technological options?, it is the goal of REMIND to explore consistent transformation pathways.
Phillip D. Alderman
Geosci. Model Dev., 14, 6541–6569, https://doi.org/10.5194/gmd-14-6541-2021, https://doi.org/10.5194/gmd-14-6541-2021, 2021
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This paper documents a framework for accessing crop model input data directly from spatially referenced file formats and running simulations in parallel across a geographic region using the Decision Support System for Agrotechnology Transfer Cropping Systems Model (a widely used crop model system). The framework greatly reduced the execution time when compared to running the standard version of the model.
Abhijeet Mishra, Florian Humpenöder, Jan Philipp Dietrich, Benjamin Leon Bodirsky, Brent Sohngen, Christopher P. O. Reyer, Hermann Lotze-Campen, and Alexander Popp
Geosci. Model Dev., 14, 6467–6494, https://doi.org/10.5194/gmd-14-6467-2021, https://doi.org/10.5194/gmd-14-6467-2021, 2021
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Timber plantations are an increasingly important source of roundwood production, next to harvest from natural forests. However, timber plantations are currently underrepresented in global land-use models. Here, we include timber production and plantations in the MAgPIE modeling framework. This allows one to capture the competition for land between agriculture and forestry. We show that increasing timber plantations in the coming decades partly compete with cropland for limited land resources.
Cited articles
Abella, J. P., Motazedi, K., Guo, J., Cousart, K., Jing, L., and Bergerson, J. A.: Petroleum Refinery Life Cycle Inventory Model PRELIM v1.4: User Guide and Technical Documentation, Department of Chemical and Petroleum Engineering, University of Calgary, https://www.ucalgary.ca/sites/default/files/teams/477/prelim-v1.4-documentation.pdf (last access: 12 November 2024), 2020.
Akram, I.: An overview of global trading patterns in the cement industry, World Cement, https://www.worldcement.com/africa-middle-east/29042013/cement_global_trading_patterns_961/ (last access: 8 September 2023), 2013.
Arvesen, A., Luderer, G., Pehl, M., Bodirsky, B. L., and Hertwich, E. G.: Deriving life cycle assessment coefficients for application in Integrated Assessment Modeling, Environ. Modell. Softw., 99, 111–125, https://doi.org/10.1016/j.envsoft.2017.09.010, 2018.
Awais, M., Vinca, A., Byers, E., Frank, S., Fricko, O., Boere, E., Burek, P., Poblete Cazenave, M., Kishimoto, P. N., Mastrucci, A., Satoh, Y., Palazzo, A., McPherson, M., Riahi, K., and Krey, V.: MESSAGEix-GLOBIOM nexus module: integrating water sector and climate impacts, Geosci. Model Dev., 17, 2447–2469, https://doi.org/10.5194/gmd-17-2447-2024, 2024.
Bataille, C., Nilsson, L., and Jotzo, F.: Industry in a net-zero emissions world: New mitigation pathways, new supply chains, modeling needs and policy implications, Energy and Climate Change, 2, 100059, https://doi.org/10.1016/j.egycc.2021.100059, 2021.
Beller, M.: Reference energy system methodology, United States, https://www.osti.gov/servlets/purl/7191575 (last access: 29 July 2024), 1976.
Bhaskar, A., Assadi, M., and Nikpey Somehsaraei, H.: Decarbonization of the Iron and Steel Industry with Direct Reduction of Iron Ore with Green Hydrogen, Energies, 13, 758, https://doi.org/10.3390/en13030758, 2020.
Cao, Z., Shen, L., Løvik, A. N., Müller, D. B., and Liu, G.: Elaborating the History of Our Cementing Societies: An in-Use Stock Perspective, Environ. Sci. Technol., 51, 11468–11475, https://doi.org/10.1021/acs.est.7b03077, 2017.
Creutzig, F., Niamir, L., Bai, X., Callaghan, M., Cullen, J., Díaz-José, J., Figueroa, M., Grubler, A., Lamb, W. F., Leip, A., Masanet, E., Mata, É., Mattauch, L., Minx, J. C., Mirasgedis, S., Mulugetta, Y., Nugroho, S. B., Pathak, M., Perkins, P., Roy, J., De La Rue Du Can, S., Saheb, Y., Some, S., Steg, L., Steinberger, J., and Ürge-Vorsatz, D.: Demand-side solutions to climate change mitigation consistent with high levels of well-being, Nat. Clim. Change, 12, 36–46, https://doi.org/10.1038/s41558-021-01219-y, 2022.
Deetman, S., Pauliuk, S., Van Vuuren, D. P., Van Der Voet, E., and Tukker, A.: Scenarios for Demand Growth of Metals in Electricity Generation Technologies, Cars, and Electronic Appliances, Environ. Sci. Technol., 52, 4950–4959, https://doi.org/10.1021/acs.est.7b05549, 2018.
Deetman, S., Marinova, S., Van Der Voet, E., Van Vuuren, D. P., Edelenbosch, O., and Heijungs, R.: Modeling global material stocks and flows for residential and service sector buildings towards 2050, J. Clean. Prod., 245, 118658, https://doi.org/10.1016/j.jclepro.2019.118658, 2020.
Deetman, S., Boer, H. S. de, van Engelenburg, M., van der Voet, E., and van Vuuren, D. P.: Projected material requirements for the global electricity infrastructure – generation, transmission, and storage, Resour. Conserv. Recy., 164, 105200, https://doi.org/10.1016/j.resconrec.2020.105200, 2021.
Dellink, R., Chateau, J., Lanzi, E., and Magné, B.: Long-term economic growth projections in the Shared Socioeconomic Pathways, Global Environ. Chang., 42, 200–214, 2017.
Després, J., Keramidas, K., Schmitz, A., Kitous, A., Schade, B., Diaz Vazquez, A., Mima, S., Russ, H., and Wiesenthal, T.: POLES-JRC model documentation. EUR 29454 EN, Publications Office of the European Union, Luxembourg, ISBN 978-92-79-97300-0, https://doi.org/10.2760/814959, 2018.
Dodds, P. E., Keppo, I., and Strachan, N.: Characterising the Evolution of Energy System Models Using Model Archaeology, Environ. Model. Asses., 20, 83–102, https://doi.org/10.1007/s10666-014-9417-3, 2015.
Eisenmenger, N., Pichler, M., Krenmayr, N., Noll, D., Plank, B., Schalmann, E., Wandl, M.-T., and Gingrich, S.: The Sustainable Development Goals prioritize economic growth over sustainable resource use: a critical reflection on the SDGs from a socio-ecological perspective, Sustain. Sci., 15, 1101–1110, https://doi.org/10.1007/s11625-020-00813-x, 2020.
European Commission: Reference Document on Best Available Techniques in the Cement and Lime Manufacturing Industries, https://eippcb.jrc.ec.europa.eu/sites/default/files/2020-03/superseded_clm_bref_1201.pdf (last access: 29 July 2024), 2001.
Eurostat (Statistical Office of the European Union): Economy-wide material flow accounts handbook: 2018 edition, Publications Office, LU, https://doi.org/10.2785/158567, 2018.
Fischer-Kowalski, M. and Hüttler, W.: Society's Metabolism: The Intellectual History of Materials Flow Analysis, Part II, 1970–1998, J. Ind. Ecol., 2, 107–136, https://doi.org/10.1162/jiec.1998.2.4.107, 1998.
Fragkos, P., Kouvaritakis, N., and Capros, P.: Incorporating Uncertainty into World Energy Modeling: the PROMETHEUS Model, Environ. Model. Assess., 20, 549–569, 2015.
Frank, S., Gusti, M., Havlík, P., Lauri, P., DiFulvio, F., Forsell, N., Hasegawa, T., Krisztin, T., Palazzo, A., and Valin, H.: Land-based climate change mitigation potentials within the agenda for sustainable development, Environ. Res. Lett., 16, 24006, https://doi.org/10.1088/1748-9326/abc58a, 2021.
Fricko, O., Havlik, P., Rogelj, J., Klimont, Z., Gusti, M., Johnson, N., Kolp, P., Strubegger, M., Valin, H., Amann, M., Ermolieva, T., Forsell, N., Herrero, M., Heyes, C., Kindermann, G., Krey, V., McCollum, D. L., Obersteiner, M., Pachauri, S., Rao, S., and Riahi, K.: The marker quantification of the Shared Socioeconomic Pathway 2: A middle-of-the-road scenario for the 21st century, Global Environ. Chang., 42, 251–267, https://doi.org/10.1016/j.gloenvcha.2016.06.004, 2017.
Fujihara, M. A., Goulart, L. C., and Moura, G.: Cultivated biomass for the pig iron industry in Brazil, in: Bioenergy – Realizing the Potential, edited by: Silveira, S., Ch. 14, Elsevier, Oxford, 189–200, https://doi.org/10.1016/B978-008044661-5/50015-5, 2005.
Gautam, M., Pandey, B., and Agrawal, M.: Chapter 8 – Carbon Footprint of Aluminum Production: Emissions and Mitigation, in: Environmental Carbon Footprints, edited by: Muthu, S. S., Butterworth-Heinemann, 197–228, https://doi.org/10.1016/B978-0-12-812849-7.00008-8, 2018.
Gerber, J.-F. and Scheidel, A.: In Search of Substantive Economics: Comparing Today's Two Major Socio-metabolic Approaches to the Economy – MEFA and MuSIASEM, Ecol. Econ., 144, 186–194, https://doi.org/10.1016/j.ecolecon.2017.08.012, 2018.
Geyer, R., Jambeck, J. R., and Law, K. L.: Production, use, and fate of all plastics ever made, Science Advances, 3, e1700782, https://doi.org/10.1126/sciadv.1700782, 2017.
Gidden, M. J., Brutschin, E., Ganti, G., Unlu, G., Zakeri, B., Fricko, O., Mitterrutzner, B., Lovat, F., and Riahi, K.: Fairness and feasibility in deep mitigation pathways with novel carbon dioxide removal considering institutional capacity to mitigate, Environ. Res. Lett., 18, 074006, https://doi.org/10.1088/1748-9326/acd8d5, 2023.
Graedel, T. E.: Material Flow Analysis from Origin to Evolution, Environ. Sci. Technol., 53, 12188–12196, https://doi.org/10.1021/acs.est.9b03413, 2019.
Guo, F., Van Ruijven, B. J., Zakeri, B., Zhang, S., Chen, X., Liu, C., Yang, F., Krey, V., Riahi, K., Huang, H., and Zhou, Y.: Implications of intercontinental renewable electricity trade for energy systems and emissions, Nat. Energy, 7, 1144–1156, https://doi.org/10.1038/s41560-022-01136-0, 2022.
Haberl, H., Wiedenhofer, D., Erb, K-H., Görg, C., and Krausmann, F.: The Material Stock–Flow–Service Nexus: A New Approach for Tackling the Decoupling Conundrum, Sustainability, 9, 1049, https://doi.org/10.3390/su9071049, 2017.
Havlík, P., Valin, H., Herrero, M., Obersteiner, M., Schmid, E., Rufino, M. C., Mosnier, A., Thornton, P. K., Böttcher, H., Conant, R. T., Frank, S., Fritz, S., Fuss, S., Kraxner, F., and Notenbaert, A.: Climate change mitigation through livestock system transitions, P. Natl. Acad. Sci. USA, 111, 3709–3714, https://doi.org/10.1073/pnas.1308044111, 2014.
Herbst, A., Toro, F., Reitze, F., and Jochem, E.: Introduction to Energy Systems Modeling, Swiss Journal of Economics and Statistics, 148, 111–135, https://doi.org/10.1007/BF03399363, 2012.
Hertwich, E. G., Ali, S., Ciacci, L., Fishman, T., Heeren, N., Masanet, E., Asghari, F. N., Olivetti, E., Pauliuk, S., Tu, Q., and Wolfram, P.: Material efficiency strategies to reducing greenhouse gas emissions associated with buildings, vehicles, and electronics – a review, Environ. Res. Lett., 14, 043004, https://doi.org/10.1088/1748-9326/ab0fe3, 2019.
Hertwich, E. G.: Increased carbon footprint of materials production driven by rise in investments, Nat. Geosci., 14, 151–155, https://doi.org/10.1038/s41561-021-00690-8, 2021.
Huppmann, D., Gidden, M., Fricko, O., Kolp, P., Orthofer, C., Pimmer, M., Kushin, N., Vinca, A., Mastrucci, A., Riahi, K., and Krey, V.: The MESSAGEix integrated assessment model and the ix modeling platform (ixmp): an open framework for integrated and cross-cutting analysis of energy, climate, the environment, and sustainable development, Environ. Modell. Softw., 112, 143–156, https://doi.org/10.1016/j.envsoft.2018.11.012, 2019.
IAI (International Aluminum Institute): Global Aluminum Cycle 2020, https://alucycle.international-aluminium.org/public-access/public-global-cycle/ (last access: 12 July 2023), 2020.
IEA: Energy Technology Transitions for Industry, https://www.iea.org/reports/energy-technology-transitions-for-industry (last access: 29 July 2024), 2009.
IEA: The Future of Petrochemicals, https://www.iea.org/reports/the-future-of-petrochemicals (last access: 29 July 2024), 2018.
IEA: Final energy demand of selected heavy industry sectors by fuel, https://www.iea.org/data-and-statistics/charts/final-energy-demand-of-selected-heavy-industry-sectors-by-fuel-2019 (last access: 12 July 2023), 2020a.
IEA: Industry direct CO2 emissions in the Sustainable Development Scenario, 2000–2030, https://www.iea.org/data-and-statistics/charts/industry-direct-co2-emissions-in-the-sustainable-development-scenario-2000-2030 (last access: September 2023), 2020b.
IEA: Iron and Steel Technology Roadmap, https://www.iea.org/reports/iron-and-steel-technology-roadmap (last access: 29 July 2024), 2020c.
IEA: Ammonia Technology Roadmap, IEA, Paris, https://www.iea.org/reports/ammonia-technology-roadmap (last access: 29 July 2024), 2021a.
IEA: World Energy Statistics and Balances, IEA [data set], https://doi.org/10.1787/data-00512-en, 2021b.
IEA: Tracking Aluminium, https://www.iea.org/energy-system/industry/aluminium (last access: 29 July 2024), 2023a.
IEA: Tracking Industry, https://www.iea.org/energy-system/industry (last access: 12 July 2023), 2023b.
IEA: Global thermal energy intensity of clinker production by fuel in the Net Zero Scenario, 2010–2030, https://www.iea.org/data-and-statistics/charts/global-thermal-energy-intensity-of-clinker-production-by-fuel-in-the-net-zero-scenario-2010-2030 (last access: 12 July 2023), 2023c.
IEA: ETP Clean Energy Technology Guide, https://www.iea.org/data-and-statistics/data-tools/etp-clean-energy-technology-guide (last access: 15 July 2024), 2023d.
IIASA-IBF: Global Biosphere Management Model (GLOBIOM) Documentation 2023, Version 1.0, https://pure.iiasa.ac.at/18996 (last access: 24 July 2024), 2023.
IPCC (Intergovernmental Panel On Climate Change): Emissions Trends and Drivers, in: Climate Change 2022 – Mitigation of Climate Change, Cambridge University Press, 215–294, https://doi.org/10.1017/9781009157926.004, 2023.
Kalt, G., Thunshirn, P., Wiedenhofer, D., Krausmann, F., Haas, W., and Haberl, H.: Material stocks in global electricity infrastructures – An empirical analysis of the power sector's stock-flow-service nexus, Resources, Conserv. Recycling, 173, 105723, https://doi.org/10.1016/j.resconrec.2021.105723, 2021.
Keramidas, K., Mima, S., and Bidaud, A.: Opportunities and roadblocks in the decarbonisation of the global steel sector: A demand and production modeling approach, Energy and Climate Change, 5, 100121, https://doi.org/10.1016/j.egycc.2023.100121, 2024.
Kermeli, K.: ADVANCE-WP2 Enhancing the representation of energy demand developments in IAM models – A modeling guide for the cement industry, http://www.fp7-advance.eu/?q=content/industrial-sector-cement-guideline (last access: 24 July 2024), 2016.
Krausmann, F., Wiedenhofer, D., Lauk, C., Haas, W., Tanikawa, H., Fishman, T., Miatto, A., Schandl, H., and Haberl, H.: Global socioeconomic material stocks rise 23-fold over the 20th century and require half of annual resource use, P. Natl. Acad. Sci. USA, 114, 1880–1885, https://doi.org/10.1073/pnas.1613773114, 2017.
Krausmann, F., Lauk, C., Haas, W., and Wiedenhofer, D.: From resource extraction to outflows of wastes and emissions: The socioeconomic metabolism of the global economy, 1900–2015, Global Environ. Chang., 52, 131–140, https://doi.org/10.1016/j.gloenvcha.2018.07.003, 2018.
Krey, V., Havlik, P., Kishimoto, P. N., Fricko, O., Zilliacus, J., Gidden, M., Strubegger, M., Kartasasmita, G., Ermolieva, T., Forsell, N., Gusti, M., Johnson, N., Kikstra, J., Kindermann, G., Kolp, P., Lovat, F., McCollum, D. L., Min, J., Pachauri, S., Parkinson, S. C., Rao, S., Rogelj, J., Ünlü, G., Valin, H., Wagner, P., Zakeri, B., Obersteiner, M., and Riahi, K.: MESSAGEix-GLOBIOM Documentation – 2020 release, https://doi.org/10.22022/IACC/03-2021.17115, 2020.
Lamb, W. F., Wiedmann, T., Pongratz, J., Andrew, R., Crippa, M., Olivier, J. G. J., Wiedenhofer, D., Mattioli, G., Khourdajie, A. A., House, J., Pachauri, S., Figueroa, M., Saheb, Y., Slade, R., Hubacek, K., Sun, L., Ribeiro, S. K., Khennas, S., De La Rue Du Can, S., Chapungu, L., Davis, S. J., Bashmakov, I., Dai, H., Dhakal, S., Tan, X., Geng, Y., Gu, B., and Minx, J.: A review of trends and drivers of greenhouse gas emissions by sector from 1990 to 2018, Environ. Res. Lett., 16, 073005, https://doi.org/10.1088/1748-9326/abee4e, 2021.
Lanau, M., Liu, G., Kral, U., Wiedenhofer, D., Keijzer, E., Yu, C., and Ehlert, C.: Taking Stock of Built Environment Stock Studies: Progress and Prospects, Environ. Sci. Technol., 53, 8499–8515, https://doi.org/10.1021/acs.est.8b06652, 2019.
Levi, P. G. and Cullen, J. M.: Mapping Global Flows of Chemicals: From Fossil Fuel Feedstocks to Chemical Products, Envir. Sci. Tech., 52, 1725–1734, https://doi.org/10.1021/acs.est.7b04573, 2018.
Liu, G., and Müller, D. B.: Centennial evolution of aluminum in-use stocks on our aluminized planet, Envir. Sci. Tech., 47, 4882–4888, https://doi.org/10.1021/es305108p, 2013.
Lopez, G., Keiner, D., Fasihi, M., Koiranen, T., and Breyer, C.: From fossil to green chemicals: sustainable pathways and new carbon feedstocks for the global chemical industry, Energ. Environ. Sci., 16, 2879–2909, 2023.
Mastrucci, A., van Ruijven, B., Byers, E., Poblete-Cazenave, M., and Pachauri, S.: Global scenarios of residential heating and cooling energy demand and CO2 emissions, Climatic Change, 168, 14, https://doi.org/10.1007/s10584-021-03229-3, 2021.
Messner, S. and Strubegger, M.: User's Guide for MESSAGE III, http://pure.iiasa.ac.at/id/eprint/4527/1/WP-95-069.pdf (last access: 20 June 2024), 1995.
Methanol Institute: Global Methanol Supply and Demand Balance, https://www.methanol.org/methanol-price-supply-demand/ (last access: 20 December 2023), 2022.
MIDREX: MIDREX NG™ with H2 Addition: Moving from natural gas to hydrogen in decarbonizing ironmaking, https://www.midrex.com/tech-article/moving-from-natural-gas-to-hydrogen-in-decarbonizing-ironmaking/ (last access: 10 July 2024), 2022.
Mission Possible Partnership: Making Net-Zero Steel Possible, https://missionpossiblepartnership.org/wp-content/uploads/2022 (last access: 10 July 2024), 2022.
Müller, A., Harpprecht, C., Sacchi, R., Maes, B., Van Sluisveld, M., Daioglou, V., Šavija, B., and Steubing, B.: Decarbonizing the cement industry: Findings from coupling prospective life cycle assessment of clinker with integrated assessment model scenarios, J. Clean. Prod., 450, 141884, https://doi.org/10.1016/j.jclepro.2024.141884, 2024.
Nakamura, S., Kondo, Y., Kagawa, S., Matsubae, K., Nakajima, K., and Nagasaka, T.: MaTrace: Tracing the Fate of Materials over Time and Across Products in Open-Loop Recycling, Environ. Sci. Technol., 48, 7207–7214, https://doi.org/10.1021/es500820h, 2014.
Neelis, M. L., Patel, M., Gielen, D. J., and Blok, K.: Modeling CO2 emissions from non-energy use with the non-energy use emission accounting tables (NEAT) model, Resour., Conserv. Recy., 45, 226–250, https://doi.org/10.1016/J.RESCONREC.2005.05.003, 2005.
OEC (Observatory of Economic Complexity): Iron and Steel, https://oec.world/en/profile/hs/iron-steel (last access: July 2023), 2022.
Orthofer, C., Huppmann, D., and Krey, V.: South Africa's shale gas resources – chance or challenge?, Frontiers in Energy Research, 7, 20, https://doi.org/10.3389/fenrg.2019.00020, 2019.
Pauliuk, S. and Hertwich, E. G.: Socioeconomic metabolism as paradigm for studying the biophysical basis of human societies, Ecol. Econ., 119, 83–93, https://doi.org/10.1016/j.ecolecon.2015.08.012, 2015.
Pauliuk, S., Wang, T., and Müller, D. B.: Steel all over the world: Estimating in-use stocks of iron for 200 countries, Resources, Conserv. Recycling, 71, 22–30, https://doi.org/10.1016/j.resconrec.2012.11.008, 2013.
Pauliuk, S., Arvesen, A., Stadler, K., and Hertwich, E. G.: Industrial ecology in integrated assessment models, Nat. Clim. Change, 7, 13–20, https://doi.org/10.1038/nclimate3148, 2017.
Plank, B., Streeck, J., Virág, D., Krausmann, F., Haberl, H., and Wiedenhofer, D.: From resource extraction to manufacturing and construction: flows of stock-building materials in 177 countries from 1900 to 2016, Resources, Conserv. Recycling, 179, 106122, https://doi.org/10.1016/j.resconrec.2021.106122, 2022.
Rao, N. D. and Min, J.: Decent Living Standards: Material Prerequisites for Human Wellbeing, Soc. Indic. Res., 138, 225–244, https://doi.org/10.1007/s11205-017-1650-0, 2018.
Riahi, K., Bertram, C., Huppmann, D., Rogelj, J., Bosetti, V., Cabardos, A.-M., Deppermann, A., Drouet, L., Frank, S., Fricko, O., Fujimori, S., Harmsen, M., Hasegawa, T., Krey, V., Luderer, G., Paroussos, L., Schaeffer, R., Weitzel, M., van der Zwaan, B., Vrontisi, Z., Longa, F. D., Després, J., Fosse, F., Fragkiadakis, K., Gusti, M., Humpenöder, F., Keramidas, K., Kishimoto, P., Kriegler, E., Meinshausen, M., Nogueira, L. P., Oshiro, K., Popp, A., Rochedo, P. R. R., Ünlü, G., van Ruijven, B., Takakura, J., Tavoni, M., van Vuuren, D., and Zakeri, B.: Cost and attainability of meeting stringent climate targets without overshoot, Nat. Clim. Change, 11, 1063–1069, https://doi.org/10.1038/s41558-021-01215-2, 2021.
Rochedo, P.: Development of a global integrated energy model to evaluate the Brazilian role in climate change mitigation scenarios, DS Thesis, Universidade Federal do Rio de Janeiro, Brazil, 2016.
Scrivener, K. L., John, V. M., and Gartner, E. M.: Eco-efficient cements: Potential economically viable solutions for a low-CO2 cement-based materials industry, Cement Concrete Res., 114, 2–26, https://doi.org/10.1016/j.cemconres.2018.03.015, 2018.
Stegmann, P., Daioglou, V., Londo, M., van Vuuren, D. P., and Junginger, M.: Plastic futures and their CO2 emissions, Nature, 612, 272–276, https://doi.org/10.1038/s41586-022-05422-5, 2022.
Stern, D. I.: The role of energy in economic growth, Ecol. Econ. Reviews, 1219, 26–51, https://doi.org/10.1111/j.1749-6632.2010.05921.x, 2011.
Streeck, J.: Triangulation of stock-flow indicators of material cycles from MESSAGEix and industrial ecology, YSSP Report, IIASA, Energy Climate and Environment Programme, Laxenburg, Austria, https://pure.iiasa.ac.at/18280 (last access: 29 July 2024), 2022.
Sugiyama, M., Wilson, C., Wiedenhofer, D., Boza-Kiss, B., Cao, T., Chatterjee, J. S., Chatterjee, S., Hara, T., Hayashi, A., Ju, Y., Krey, V., Godoy León, M. F., Martinez, L., Masanet, E., Mastrucci, A., Min, J., Niamir, L., Pelz, S., Roy, J., Saheb, Y., Schaeffer, R., Ürge-Vorsatz, D., van Ruijven, B., Shimoda, Y., Verdolini, E., Wiese, F., Yamaguchi, Y., Zell-Ziegler, C., and Zimm, C.: High with low: Harnessing the power of demand-side solutions for high wellbeing with low energy and material demand, Joule, 8, 1–6, https://doi.org/10.1016/j.joule.2023.12.014, 2024.
UNEP (United Nations Environment Programme): The use of natural resources in the economy: a global manual on economy wide material flow accounting, https://wedocs.unep.org/20.500.11822/36253 (last access: 12 July 2024), 2023.
UNEP (United Nations Environment Programme) and IRP (International Resource Panel): Global Material Flows Database, UNEP (United Nations Environment Programme) and IRP (International Resource Panel): Global Material Flows Database [data set], https://www.resourcepanel.org/global-material-flows-database (last access: 29 July 2024), 2023.
Ünlü, G., Maczek, F., Min, J., Frank, S., Fridolin, G., Kishimoto, P. N., Streeck, J., Eisenmenger, N., Wiedenhofer, D., and Krey, V.: MESSAGEix-Materials (1.1.0), Zenodo [code and data set], https://doi.org/10.5281/zenodo.13121819, 2024.
van Ruijven, B. J., van Vuuren, D. P., Boskaljon, W., Neelis, M. L., Saygin, D., and Patel, M. K.: Long-term model-based projections of energy use and CO2 emissions from the global steel and cement industries, Resources, Conserv. Recycling, 112, 15–36, https://doi.org/10.1016/j.resconrec.2016.04.016, 2016.
van Sluisveld, M. A. E., de Boer, H. S., Daioglou, V., Hof, A. F., and van Vuuren, D. P.: A race to zero – Assessing the position of heavy industry in a global net-zero CO2 emissions context, Energy and Climate Change, 2, 100051, https://doi.org/10.1016/j.egycc.2021.100051, 2021.
Vélez-Henao, J. A. and Pauliuk, S.: Material Requirements of Decent Living Standards, Environ. Sci. Technol., 57, 14206–14217, https://doi.org/10.1021/acs.est.3c03957, 2023.
Viebahn, P., Nitsch, J., Fischedick, M., Esken, A., Schüwer, D., Supersberger, N., Zuberbühler, U., and Edenhofer, O.: Comparison of carbon capture and storage with renewable energy technologies regarding structural, economic, and ecological aspects in Germany, Int. J. Greenh. Gas Con., 1, 121–133, https://doi.org/10.1016/S1750-5836(07)00024-2, 2007.
Virág, D., Wiedenhofer, D., Baumgart, A., Matej, S., Krausmann, F., Min, J., Rao, N. D., and Haberl, H.: How much infrastructure is required to support decent mobility for all? An exploratory assessment, Ecol. Econ., 200, 107511, https://doi.org/10.1016/j.ecolecon.2022.107511, 2022.
Watari, T., Cao, Z., Hata, S., and Nansai, K.: Efficient use of cement and concrete to reduce reliance on supply-side technologies for net-zero emissions, Nat. Commun., 13, 4158, https://doi.org/10.1038/s41467-022-31806-2, 2022.
Wiedenhofer, D., Fishman, T., Lauk, C., Haas, W., and Krausmann, F.: Integrating Material Stock Dynamics Into Economy-Wide Material Flow Accounting: Concepts, Modeling, and Global Application for 1900–2050, Ecol. Econ., 156, 121–133, https://doi.org/10.1016/j.ecolecon.2018.09.010, 2019.
Wiedenhofer, D., Streeck, J., Wiese, F., Verdolini, E., Mastrucci, A., Ju, Y., Boza-kiss, B., Min, J., Norman, J., Wieland, H., Bento, N., Fernanda, M., León, G., Magalar, L., Mayer, A., Gingrich, S., Hayashi, A., Jupesta, J., Ünlü, G., Niamir, L., Cao, T., Zanon-zotin, M., Plank, B., Vélez-henao, J., Masanet, E., and Krey, V.: Industry Transformations for High Service Provisioning with Lower Energy and Material Demand: A Review of Models and Scenarios, 249–279, 2024a.
Wiedenhofer, D., Streeck, J., Wieland, H., Grammer, B., Baumgart, A., Plank, B., Helbig, C., Pauliuk, S., Haberl, H., and Krausmann, F.: From Extraction to End-uses and Waste Management: Modelling Economy-wide Material Cycles and Stock Dynamics Around the World, J. Ind. Ecol., 1–17, https://doi.org/10.2139/ssrn.4794611, 2024b.
World Steel Association: World Steel in Figures, https://www.worldsteel.org/steel-by-topic/statistics/World-Steel-in-Figures.html (last access: 26 January 2021), 2020.
Worrell, E., Allwood, J., and Gutowski, T.: The Role of Material Efficiency in Environmental Stewardship, Annu. Rev. Environ. Resour., 41, 575–598, https://doi.org/10.1146/annurev-environ-110615-085737, 2016.
Yara: Fertilizer Industry Handbook, https://www.yara.com/siteassets/investors/057-reports-and-presentations/other/2018/fertilizer-industry-handbook-2018.pdf/ (last access: 12 July 2024), 2018.
Zhou, W., McCollum, D. L., Fricko, O., Gidden, M., Huppmann, D., Krey, V., and Riahi, K.: A comparison of low carbon investment needs between China and Europe in stringent climate policy scenarios, Environ. Res. Lett., 14, 054017, https://doi.org/10.1088/1748-9326/ab0dd8, 2019.
Short summary
Extraction and processing of raw materials constitute a significant source of CO2 emissions in industry and so are contributors to climate change. We develop an open-source tool to assess different industry decarbonization pathways in integrated assessment models (IAMs) with a representation of material flows and stocks. We highlight the importance of expanding the scope of climate change mitigation options to include circular-economy and material efficiency measures in IAM scenario analysis.
Extraction and processing of raw materials constitute a significant source of CO2 emissions in...
